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Record W2887808077 · doi:10.1136/bmjebm-2018-110975

Meta-analysis suggests that metformin may reduce pre-eclampsia compared with insulin use during pregnancy

2018· letter· en· W2887808077 on OpenAlexaff
Denice S. Feig

Bibliographic record

VenueBMJ evidence-based medicine · 2018
Typeletter
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMetforminMedicinePolycystic ovaryEclampsiaGestational diabetesPregnancyObstetricsPreeclampsiaType 2 diabetesDiabetes mellitusMeta-analysisInsulinInsulin resistanceInternal medicineEndocrinologyGestationBiology

Abstract

fetched live from OpenAlex

Commentary on : Alqudah A, McKinley MC, McNally R et al Risk of pre-eclampsia in women taking metformin: a systematic review and meta-analysis. Diabet Med 2018;35:160–172. Pre-eclampsia occurs in 2%–5% of pregnancies and is an important cause of maternal and fetal morbidity and mortality. The risk of pre-eclampsia increases 2.9 fold in obese women and 4.47 fold in women with glucose intolerance, and is therefore of particular concern in these populations. Metformin has been studied in three populations during pregnancy: women with polycystic ovary syndrome (PCOS), women with glucose intolerance (gestational diabetes (GDM) and occasionally women with type 2 diabetes (T2DM)) and in obese pregnant women. However, the effect of metformin on pre-eclampsia remains unclear, with variable results in all three populations. In the two randomised controlled trials (RCTs) of metformin use in obese women, one showed a significant reduction in pre-eclampsia while the other showed no difference. Results in women with PCOS have been conflicting …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Meta-analysislow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Meta-analysislow
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.269
GPT teacher head0.372
Teacher spread0.103 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2018
Admission routes1
Has abstractyes

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